| --- |
| license: other |
| base_model: MiniMaxAI/MiniMax-M2.5 |
| tags: |
| - gguf |
| - quantized |
| - apex |
| - moe |
| - mixture-of-experts |
| - minimax |
| --- |
| |
| # MiniMax-M2.5 APEX GGUF |
|
|
| **APEX (Adaptive Precision for EXpert Models)** quantizations of [MiniMax-M2.5](https://huggingface.co/MiniMaxAI/MiniMax-M2.5). |
|
|
| **Brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team** | [APEX Project](https://github.com/mudler/apex-quant) | [Technical Report](https://github.com/mudler/apex-quant/blob/main/paper/APEX_Technical_Report.pdf) |
|
|
| ## Benchmark Results |
|
|
| Benchmarks coming soon. For reference APEX benchmarks on the Qwen3.5-35B-A3B architecture, see [mudler/Qwen3.5-35B-A3B-APEX-GGUF](https://huggingface.co/mudler/Qwen3.5-35B-A3B-APEX-GGUF). |
|
|
| ## Available Files |
|
|
| | File | Profile | Size | Best For | |
| |------|---------|------|----------| |
| | MiniMax-M2.5-APEX-I-Balanced.gguf | I-Balanced | 155 GB | Best overall quality/size ratio | |
| | MiniMax-M2.5-APEX-I-Quality.gguf | I-Quality | 130 GB | Highest quality with imatrix | |
| | MiniMax-M2.5-APEX-Quality.gguf | Quality | 130 GB | Highest quality standard | |
| | MiniMax-M2.5-APEX-Balanced.gguf | Balanced | 155 GB | General purpose | |
| | MiniMax-M2.5-APEX-I-Compact.gguf | I-Compact | 100 GB | Multi-GPU setups, best quality/size | |
| | MiniMax-M2.5-APEX-Compact.gguf | Compact | 100 GB | Multi-GPU setups | |
| | MiniMax-M2.5-APEX-I-Mini.gguf | I-Mini | 81 GB | Smallest viable | |
|
|
| ## What is APEX? |
|
|
| APEX is a quantization strategy for Mixture-of-Experts (MoE) models. It classifies tensors by role (routed expert, shared expert, attention) and applies a layer-wise precision gradient -- edge layers get higher precision, middle layers get more aggressive compression. I-variants use diverse imatrix calibration (chat, code, reasoning, tool-calling, agentic traces, Wikipedia). |
|
|
| See the [APEX project](https://github.com/mudler/apex-quant) for full details, technical report, and scripts. |
|
|
| ## Architecture |
|
|
| - **Model**: MiniMax-M2.5 (MiniMaxM2) |
| - **Layers**: 62 |
| - **Experts**: 256 routed + 1 shared (8 active per token) |
| - **Total Parameters**: 228.7B |
| - **Active Parameters**: ~45B per token |
| - **APEX Config**: 5+5 symmetric edge gradient across 62 layers |
| - **Calibration**: v1.3 diverse dataset (chat, code, reasoning, multilingual, tool-calling, Wikipedia) |
|
|
| ## Run with LocalAI |
|
|
| ```bash |
| local-ai run mudler/MiniMax-M2.5-APEX-GGUF@MiniMax-M2.5-APEX-I-Balanced.gguf |
| ``` |
|
|
| ## Credits |
|
|
| APEX is brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team. Developed through human-driven, AI-assisted research. Built on [llama.cpp](https://github.com/ggerganov/llama.cpp). |
|
|
